Co-scheduling of HVAC control, EV charging and battery usage for building energy efficiency

Tianshu Wei, Qi Zhu, Mehdi Maasoumy

Research output: Contribution to journalConference articlepeer-review

18 Scopus citations

Abstract

Building stock consumes 40% of primary energy consumption in the United States. Among various types of energy loads in buildings, HVAC (heating, ventilation, and air conditioning) and EV (electric vehicle) charging are two of the most important ones and have distinct characteristics. HVAC system accounts for 50% of the building energy consumption and typically operates throughout the day, while EV charging is an emerging major energy load that is hard to predict and may cause spikes in energy demand. To maximize building energy efficiency and grid stability, it is important to address both types of energy loads in a holistic framework. Furthermore, on the supply side, the utilization of multiple energy sources such as grid electricity, solar, wind, and battery storage provides more opportunities for energy efficiency, and should be considered together with the scheduling of energy loads. In this paper, we present a novel model predictive control (MPC) based algorithm to co-schedule HVAC control, EV scheduling and battery usage for reducing the total building energy consumption and the peak energy demand, while maintaining the temperature within the comfort zone for building occupants and meeting the deadlines for EV charging. Experiment results demonstrate the effectiveness of our approach under a variety of demand, supply and environment constraints.

Original languageEnglish (US)
Article number7001351
Pages (from-to)191-196
Number of pages6
JournalIEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
Volume2015-January
Issue numberJanuary
DOIs
StatePublished - Jan 1 2015
Event2014 33rd IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2014 - San Jose, United States
Duration: Nov 2 2014Nov 6 2014

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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